Does it work in tensorflow v1.0.0?

[yt7589]

It is a great library. But when I use tensorflow v1.0.0 it didn't work.

My code: class FcvImgSeg(object): def init(self): print('init') self.slim = tf.contrib.slim self.fcv_ckpt_path = './models/lcct/model_fcn8s_final.ckpt' self.number_of_classes = 21 self.img_filename = './work/cat.jpg'

def seg_img_fcv(self, img_filename):
    print('segmentation image by fully convalutional vgg v0.0.4')
    img_filename_plhr = tf.placeholder(tf.string)
    fcv_feed_dict = {img_filename_plhr: img_filename}
    img_content = tf.read_file(img_filename_plhr)
    img_tensor = tf.image.decode_jpeg(img_content, channels=3)
    image_batch_tensor = tf.expand_dims(img_tensor, axis=0)
    fcn_8s = adapt_network_for_any_size_input(FCN_8s, 32)
    pred, fcn_16s_variables_mapping = FCN_8s(image_batch_tensor=image_batch_tensor,
                                      number_of_classes=self.number_of_classes,
                                      is_training=False)
    initializer = tf.local_variables_initializer()
    saver = tf.train.Saver()
    with tf.Session() as sess:
        sess.run(initializer)
        saver.restore(sess, "/home/dpakhom1/tf_projects/segmentation/model_fcn8s_final.ckpt")
        image_np, pred_np = sess.run([img_tensor, pred], feed_dict=fcv_feed_dict)
        io.imshow(image_np)
        io.show()
        io.imshow(pred_np.squeeze())
        io.show()

It reported errors as below:

Traceback (most recent call last): File "exp.py", line 24, in test() File "exp.py", line 12, in test fcv_img_seg.seg_img_fcv('e:\awork\dlp\work\lcct\cat.jpg') File "E:\awork\dlp\apps\lcct\fcv_img_seg.py", line 45, in seg_img_fcv is_training=False) File "./lib/tfis\tf_image_segmentation\models\fcn_8s.py", line 81, in FCN_8s fc_conv_padding='SAME') File "./lib\fcv\models\slim\nets\vgg.py", line 166, in vgg_16 net = slim.repeat(inputs, 2, slim.conv2d, 64, [3, 3], scope='conv1') File "E:\software\Anaconda3\envs\wky351\lib\site-packages\tensorflow\contrib\layers\python\layers\layers.py", line 1735, in repeat outputs = layer(outputs, *args, **kwargs) File "E:\software\Anaconda3\envs\wky351\lib\site-packages\tensorflow\contrib\framework\python\ops\arg_scope.py", line 177, in func_with_args return func(*args, **current_args) File "E:\software\Anaconda3\envs\wky351\lib\site-packages\tensorflow\contrib\layers\python\layers\layers.py", line 907, in convolution outputs = layer.apply(inputs) File "E:\software\Anaconda3\envs\wky351\lib\site-packages\tensorflow\python\layers\base.py", line 323, in apply return self.call(inputs, **kwargs) File "E:\software\Anaconda3\envs\wky351\lib\site-packages\tensorflow\python\layers\base.py", line 289, in call self.build(input_shapes[0]) File "E:\software\Anaconda3\envs\wky351\lib\site-packages\tensorflow\python\layers\convolutional.py", line 145, in build dtype=self.dtype) File "E:\software\Anaconda3\envs\wky351\lib\site-packages\tensorflow\python\ops\variable_scope.py", line 1034, in get_variable use_resource=use_resource, custom_getter=custom_getter) File "E:\software\Anaconda3\envs\wky351\lib\site-packages\tensorflow\python\ops\variable_scope.py", line 933, in get_variable use_resource=use_resource, custom_getter=custom_getter) File "E:\software\Anaconda3\envs\wky351\lib\site-packages\tensorflow\python\ops\variable_scope.py", line 349, in get_variable validate_shape=validate_shape) File "E:\software\Anaconda3\envs\wky351\lib\site-packages\tensorflow\python\layers\base.py", line 278, in variable_getter variable_getter=functools.partial(getter, **kwargs)) File "E:\software\Anaconda3\envs\wky351\lib\site-packages\tensorflow\python\layers\base.py", line 228, in _add_variable trainable=trainable and self.trainable) File "E:\software\Anaconda3\envs\wky351\lib\site-packages\tensorflow\contrib\layers\python\layers\layers.py", line 1325, in layer_variable_getter return _model_variable_getter(getter, *args, **kwargs) File "E:\software\Anaconda3\envs\wky351\lib\site-packages\tensorflow\contrib\layers\python\layers\layers.py", line 1314, in _model_variable_getter custom_getter=getter) File "E:\software\Anaconda3\envs\wky351\lib\site-packages\tensorflow\contrib\framework\python\ops\arg_scope.py", line 177, in func_with_args return func(*args, **current_args) File "E:\software\Anaconda3\envs\wky351\lib\site-packages\tensorflow\contrib\framework\python\ops\variables.py", line 255, in model_variable partitioner=partitioner, custom_getter=custom_getter) File "E:\software\Anaconda3\envs\wky351\lib\site-packages\tensorflow\contrib\framework\python\ops\arg_scope.py", line 177, in func_with_args return func(*args, **current_args) File "E:\software\Anaconda3\envs\wky351\lib\site-packages\tensorflow\contrib\framework\python\ops\variables.py", line 212, in variable partitioner=partitioner) File "E:\software\Anaconda3\envs\wky351\lib\site-packages\tensorflow\python\ops\variable_scope.py", line 341, in _true_getter use_resource=use_resource) File "E:\software\Anaconda3\envs\wky351\lib\site-packages\tensorflow\python\ops\variable_scope.py", line 711, in _get_single_variable validate_shape=validate_shape) File "E:\software\Anaconda3\envs\wky351\lib\site-packages\tensorflow\python\ops\variables.py", line 197, in init expected_shape=expected_shape) File "E:\software\Anaconda3\envs\wky351\lib\site-packages\tensorflow\python\ops\variables.py", line 275, in _init_from_args initial_value(), name="initial_value", dtype=dtype) File "E:\software\Anaconda3\envs\wky351\lib\site-packages\tensorflow\python\ops\variable_scope.py", line 687, in shape.as_list(), dtype=dtype, partition_info=partition_info) TypeError: init() got multiple values for argument 'dtype'

[nealmcb]

Looks like #20 and #8 are relevant, given the significant changes in the API for Tensorflow 1.0. Perhaps the PR there will help: Fix for #8: make forward/backward compatible with tf-1.0.x..

[ahundt]

try applying my pull request, I'm running it on tf 1.1 https://github.com/warmspringwinds/tf-image-segmentation/pull/7